日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2403.09865

Safety-Critical Control for Autonomous Systems: Control Barrier Functions via Reduced-Order Models

Safety-Critical Control for Autonomous Systems: Control Barrier Functions via Reduced-Order Models

シェア:XThreadsFacebookLINEはてブBluesky

著者: Max H. Cohen, Tamas G. Molnar, Aaron D. Ames

分類: eess.SY, cs.RO, cs.SY

原文アブストラクト

Modern autonomous systems, such as flying, legged, and wheeled robots, are generally characterized by high-dimensional nonlinear dynamics, which presents challenges for model-based safety-critical control design. Motivated by the success of reduced-order models in robotics, this paper presents a tutorial on constructive safety-critical control via reduced-order models and control barrier functions (CBFs). To this end, we provide a unified formulation of techniques in the literature that share a common foundation of constructing CBFs for complex systems from CBFs for much simpler systems. Such ideas are illustrated through formal results, simple numerical examples, and case studies of real-world systems to which these techniques have been experimentally applied.